/research-pipeline

name: research-pipeline
description: "Full end-to-end research pipeline: from a broad research direction through idea discovery, experiments, and review all the way to a polished paper PDF. Use when user says \"全流程\", \"full pipeline\", \"从找idea到投稿\", \"end-to-end research\", or wants the complete autonomous research lifecycle."
argument-hint: "[research-direction] [— resume <run_id>]"
allowed-tools: Bash(*), Read, Write, Edit, Grep, Glob, WebSearch, WebFetch, Skill, mcp__codex__codex, mcp__codex__codex-reply

Full Research Pipeline: Idea → Experiments → Submission

> **Before each reviewer slot**, follow [Selectable Reviewers](../shared-references/reviewer-backends.md): > resolve invocation → `.aris/reviewer.json` → Claude Code default (Codex MCP) > with `reviewer_route.py` through the canonical helper resolver, preserving this > slot's tier, fresh contexts, source/image inputs and deterministic gates. > Codex examples/pins below apply only to `backend=codex`; other routes use their > own first-call/reply contract. Save the route and actual returned identity; > unavailable selections are `REVIEW_UNAVAILABLE`. Classify acceptance from actual > families/completion/scope. Forward invocation reviewer/model/effort overrides > to reviewer-bearing children. Generation workers are unchanged.

> ⏱ **External cadence: non-judgmental heartbeat only.** An overnight `/loop` / > `CronCreate` heartbeat may wake, detect a **stalled** phase (no progress, dead > process, blocked on a freed resource) and **nudge** it forward — it may NEVER > decide the work is good (paper good enough, proof holds, claim supported). > Every such verdict stays on its own skill's internal cadence and terminates in > the cross-model jury. A heartbeat may say "keep going," never "good enough." > See > [`shared-references/external-cadence.md`](../shared-references/external-cadence.md) > (overnight-pipeline rule + stall detection & forced structural pivot). At heartbeat > startup, touch the run state first each tick and register this run with the watchdog > `loop` type (so a silent death surfaces as STALE); unregister on completion. The > watchdog only detects — it never acquits. Each tick also record the new-finding count > via the `iteration_log.py` helper (resolve through the canonical > `.aris/tools → tools → $ARIS_REPO/tools → $ARIS_REPO/tools via ~/.aris/repo` > chain, integration-contract §2; warn-and-skip if unresolved): > `python3 "$ITER_LOG" note <root> <run_id> <phase> <n>`. On the returned > `pivot=structural` (stale ≥ 2) the nudge must change a STRUCTURAL constraint and pick an > untried direction; on `pivot=human` (stale ≥ 4) flag for attention. Counting only — > never a quality verdict.

End-to-end autonomous research workflow for: **$ARGUMENTS**

Optional formal proof route

Before creating an experimental run, route theorem-centered requests for Lean to [`/lean-formalize`](../lean-formalize/SKILL.md) and report its actual proof result. Run the experimental stages below when the task includes empirical research. In a mixed project, use Lean for a user-requested formal proof or a specific mathematical obligation whose formal verification would materially help; return its checked scope and remaining obligations to the research summary and applicable proof audit. Ordinary mathematics stays in the existing theory skills. Difficulty alone does not make Lean mandatory, and a formal sublemma does not establish an empirical claim.

Constants

• **AUTO_PROCEED = true** — When `true`, every selection checkpoint is informational: report the choice and continue in the same turn. When `false`, ask for explicit user confirmation and end the turn at the checkpoint.
• **ARXIV_DOWNLOAD = false** — When `true`, `/research-lit` downloads the top relevant arXiv PDFs during literature survey. When `false` (default), only fetches metadata via arXiv API. Passed through to `/idea-discovery` → `/research-lit`.
• **HUMAN_CHECKPOINT = false** — When `true`, the auto-review loops (Stage 3) pause after each round's review to let you see the score and provide custom modification instructions before fixes are implemented. When `false` (default), loops run fully autonomously. Passed through to `/auto-review-loop`.
• **REVIEWER_DIFFICULTY = medium** — How adversarial the reviewer is. `medium` (default): standard MCP review. `hard`: adds reviewer memory + debate protocol. `nightmare`: GPT reads repo directly via `codex exec` + memory + debate. Passed through to `/auto-review-loop`.
• **CODE_REVIEW = true** — GPT-6-Astra xhigh reviews experiment code before deployment. Catches logic bugs before wasting GPU hours. Set `false` to skip. Passed through to `/experiment-bridge`.
• **BASE_REPO = false** — GitHub repo URL to use as base codebase. When set, `/experiment-bridge` clones the repo first and implements experiments on top of it. When `false` (default), writes code from scratch or reuses existing project files. Passed through to `/experiment-bridge`.
• **COMPACT = false** — When `true`, generates compact summary files for short-context models and session recovery. Passed through to `/idea-discovery` and `/experiment-bridge`.
• **AUTO_WRITE = false** — When `true`, automatically invoke Workflow 3 (`/paper-writing`) after Stage 4. `VENUE` is needed only when Stage 5 begins — a missing venue defers paper writing; it never blocks Stages 1-4. When `false` (default), Stage 4 generates `NARRATIVE_REPORT.md` and stops — user invokes `/paper-writing` manually.
• **VENUE = (unset)** — Target venue for paper writing; bound only when Stage 5 begins. Options: `ICLR`, `NeurIPS`, `ICML`, `CVPR`, `ACL`, `AAAI`, `ACM`, `IEEE_CONF`, `IEEE_JOURNAL`. No default: a missing venue defers paper writing — it never blocks Stages 1-4 and is never guessed.
• **RENDER_HTML = true** — When `true` (default), auto-render `NARRATIVE_REPORT.md` to HTML at Stage 4 completion via `/render-html`. Uses `--no-review` (this is an internal handoff doc to `/paper-writing